Cargo selection, route planning, and speed optimization in tramp shipping under carbon intensity indicator (CII) regulations

To mitigate the significant environmental impacts of the shipping industry, the International Maritime Organization (IMO) introduced the Carbon Intensity Indicator (CII), which measures CO2 emissions per unit of cargo-carrying capacity and distance traveled. While the implementation of energy-efficient technologies is crucial for meeting CII regulations, these advancements often entail substantial investment costs. Consequently, optimizing operations has become a more practical short-term approach; however, operational adjustments made solely to comply with CII regulations may also have unintended adverse effects. To address this issue, this research develops a pick up and delivery optimization model for tramp ships, which operate on irregular schedules and routes, to minimize total emissions and costs while complying with CII regulations. The model investigates the combination of cargo selection, route planning, and speed optimization, reflecting the comprehensive and unique characteristics of tramp shipping. The problem is solved using Danzig-Wolfe decomposition and a branch-and-price algorithm, with the CII regulations being met in the pricing problem through a customized heuristic. Numerical results demonstrate that the proposed approach can find optimal or near-optimal solutions within a short time. Various experiments explore the effects of CII regulations on tramp shipping operations, environmental performances, and economic benefits. The results indicate that demand-based CII and stricter CII regulations cause ships to carry fewer cargoes, sail shorter ballast distances, reduce speed, and increase load on board. This ultimately reduces CO2 emissions but also lowers total profits. The findings assist industry stakeholders in complying with stringent environmental regulations and aid policymakers in designing targeted regulatory policies, thereby promoting sustainable maritime transport.